The effect of climate change on soil moisture content of Maize farm using data from the fifth report and SWAP model

The soil moisture estimation is essential for optimal water and soil resources management. Surface moisture is an important variable in nature's water cycle, which plays an important role in the global equilibrium of water and energy due to its impact on hydrological, ecological and meteorological processes. Therefore, in this study, soil moisture simulation in the upcoming period (2020-2039) was compared to the base period (1992-1992) from the Faroub maize farm located in Neishabour plain. The climate data was estimated using six GCM models and two RCP4.5 and RCP8.5 release scenarios. The LARS-WG model was quantified using SWAP model. The results of the change in climate parameters showed that the minimum and maximum temperatures for AOGCM models in the upcoming period will increase compared to the base period, and in some models the future rainfall will decrease compared to the base period and the RCP8.5 scenario shows a higher increase compared to RCP4.5. Changes in soil moisture at a depth of 30 cm showed that the moisture content in the soil in the upcoming periods of 2020-2039 compared with the base period for each two-year period is negligible however, the RCP8.5 scenario shows lower moisture content than RCP4.5 scenario for the six AOGCM models. Estimated annual moisture values showed that in RCP4.5 scenarios at 30 cm depth of the IPSL model, the lowest moisture content and GISS-ES-R and GFDL models had the highest annual moisture content and for RCP8.5 at depths of 30 Centimeters GFDL Model and GISS-ES-R model have the lowest moisture content and the highest annual moisture content during the weeks after plant growth.